Invited Talks:

Mariano
Consens research interests are in the areas of Data Management and the
Web, with a focus on linked data, privacy, analytics for semistructured
data, XML searching, and autonomic systems. His publications include
journal publications selected from best conference papers and several
patents. Mariano received his PhD and MSc degrees in Computer Science
from the University of Toronto. He also holds a Computer Systems
Engineer degree from the Universidad de la Republica, Uruguay. Consens
is a University of Toronto faculty member and a Visiting Scientist at
the IBM Center for Advanced Studies in Toronto. In addition, he has
been active in the software industry as a founder and CTO of a couple
of software startups, and as a Visiting Scientist at Yahoo! Research
Barcelona.

David
is retained by several governments to advise on open government and
open data, works with two spin-offs of the Harvard Negotiation Project
and advises businesses on open source strategies and community
management.

Panel:

10 minutes talk: Technical challenges for linked open cities -
As more and more cities around the world open their data and provide
data catalogs, data integration challenges emerge. The development of
applications reusing data from various catalogs require a uniform
access interface, common identifiers, and shared metadata. I will show
that semantic technologies provide a coherent set of solutions to these
challenges, and will present the problems toward their adoption.

Pr. Marc S. Fox, Professor
of Industrial Engineering and past holder of the NSERC Industrial
Research Chair in Enterprise Integration at the University of Toronto
where his research focuses on Enterprise Integration and Artificial
Intelligence.

10 minutes talk: 311NG: Next Generation Information Services for Smart Cities
- This talk will review the 311NG project which has just begun at the
University of Toronto in conjunction the City of Toronto. It will
review the goals of the project and recent work on Municipal Ontologies.

10 minutes talk: Applying Stream Processing to different domains, including transportation, finance, energy, telecommunications, etc.
Some of these areas, especially transportation and energy, fall under
the aegis of IBM's Smarter Planet initiative, whose ads you would have
definitely seen if you were watching the US Open or if you had flown
out of an airport in the US recently. The basic challenge in all these
domains is how do you process giganormous amounts of data being
produced by different sensors or other sources in real-time, and how do
you extract or produce relevant information and knowledge that can be
acted upon by decision makers. Also, how do you apply different kinds
of reusable analytics on this streaming data for purposes of
classification, prediction, simulation, rule-based analysis, etc.? How
do you balance various competing requirements in designing stream
processing applications like throughput, latency, memory and cpu
requirements, fault-tolerance, cost (in dollars) and development effort?

Description

Cities around the world aspire to provide superior
quality of life to their citizens. Furthermore, many are also seen as
centers of unique opportunities, like business, fashion, entertainment and
governance, for their citizens. Cities want to retain such preeminent
positions or re-position themselves for newer opportunities. But, resources
needed to reach and sustain such aspirations are decreasing while the
expectations continue to rise from an increasing population-base. A
positive trend of the internet age is that more data than even before is
open and accessible, including from governments at all levels of
jurisdiction, which enables rigorous analysis.

The scientific community has responded to city challenges by promoting the
computational sustainability vision where resources consumed by a city,
such as water, energy, land, food and air, can be monitored to know the
accurate present picture and then optimized for resource efficiency without
degrading quality of services it provides – traffic movement, water
availability, sanitation, public safety, etc. Industry has joined the
vision with a “smart” or “intelligent” prefix for cyber-physical systems
which involve sensing the data through physical instruments,
interconnecting and integrating them from multiple sources and analyzing
them for intelligent patterns. This effort needs access to city data,
semantic models to abstract city domains as well as interconnect them so
that advanced applications can be built by rest of the world. We will like
to call cities that enable such capabilities as, “semantic cities”.

In a Semantic City, available resources are harnessed safely, sustainably
and efficiently to achieve positive, measurable economic and societal
outcomes. Enabling City information as a utility, through a robust
(expressive, dynamic, scalable) and (critically) a sustainable technology
and socially synergistic ecosystem could drive significant benefits and
opportunities. Data (and then information and knowledge) from people,
systems and things is the single most scalable resource available to City
stakeholders to reach the objective of semantic cities.

Two major trends are supporting semantic cities – open data and semantic
web. “Open data is the idea that data should be accessible from
everyone to use and republish as they wish, without restrictions from
copyright, patents or other mechanisms of control1.” A number of cities and
government have made their data publicly available, prominent being London
(UK), Chicago (USA), Washington DC (USA), Dublin (Ireland). Semantic web as
the technology to inter-connect heterogeneous data has matured and it is
being increasing used in the form of Linked Open Data and formal
ontologies. Thus, a playfield for more AI research-driven technologies for
cities has emerged e.g., scalable, efficient, robust, optimal AI techniques.

In this context, the aims of the workshop are to:
1. Draw the attention of the AI community to the research challenges and
opportunities in semantic cities.
2. Draw the attention on the multi-disciplinary dimension and its impact on
semantic cities e.g., transportation, energy, water management
3. Identify unique issues of this domain and what new techniques may be
needed. As example, since governments and citizens are involved, data
security and privacy are first-class concerns.
4. Promoting more cities to become semantic cities
5. Elaborating a (semantic data) benchmark for testing AI techniques on
semantic cities
6. Provide a platform for sharing best-practices and discussion

Workshop Plan

Workshop Format: The workshop will consist of papers and poster
presentations, a panel, an invited talk, and discussion sessions, in a one
full day schedule. The invited talk will invite a leading expert in the
field to present their research and vision of future work. The panel will
focus on connecting the AI researchers to the various challenges that the
targeted domain brings.

Submission Guidelines:Allpapers submissions must be in AAAI format.
They can be one of two types. The first is regular research papers which
can be up to 6 pages long and are expected to present a significant
contribution. The second is short submission of up to 4 pages which
describes a position on the topic of the workshop or a demonstration/tool.